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KDD
2006
ACM

Recommendation method for extending subscription periods

11 years 3 months ago
Recommendation method for extending subscription periods
Online stores providing subscription services need to extend user subscription periods as long as possible to increase their profits. Conventional recommendation methods recommend items that best coincide with user's interests to maximize the purchase probability, which does not necessarily contribute to extend subscription periods. We present a novel recommendation method for subscription services that maximizes the probability of the subscription period being extended. Our method finds frequent purchase patterns in the long subscription period users, and recommends items for a new user to simulate the found patterns. Using survival analysis techniques, we efficiently extract information from the log data for finding the patterns. Furthermore, we infer user's interests from purchase histories based on maximum entropy models, and use the interests to improve the recommendations. Since a longer subscription period is the result of greater user satisfaction, our method benefit...
Tomoharu Iwata, Kazumi Saito, Takeshi Yamada
Added 30 Nov 2009
Updated 30 Nov 2009
Type Conference
Year 2006
Where KDD
Authors Tomoharu Iwata, Kazumi Saito, Takeshi Yamada
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